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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Search for a heavy resonance decaying to a top quark and a vector-like top quark in the lepton + jets final state in pp collisions at $\sqrt{s} = 13\,\text {TeV} $

Here a search is presented for a heavy spin-1 resonance $\mathrm {Z}'$ decaying to a top quark and a vector-like top quark partner $\text {T} $ in the lepton + jets final state. The search is performed using a data set of $\mathrm {p}$ $\mathrm {p}$ collisions at a centre-of-mass energy of 13 $\,\text {TeV}$ corresponding to an integrated luminosity of $35.9{\,\text {fb}^{-1}} $ as recorded by the CMS experiment at the CERN LHC in the year 2016. The analysis is optimised for final states arising from the $\text {T} $ decay modes to a top quark and a Higgs or $\mathrm {Z}$ boson ( $\text {T} \rightarrow \mathrm {H} \mathrm {t}, \mathrm {Z} \mathrm {t}$ ). The event selection makes use of resolved and merged top quark decay products, as well as decays of boosted Higgs bosons and $\mathrm {Z}$ and $\mathrm {W}$ bosons using jet substructure techniques. No significant deviation from the standard model background expectation is observed. Exclusion limits on the product of the cross section and branching fraction for $\mathrm {Z}'\rightarrow \mathrm {t}\text {T}, \text {T} \rightarrow \mathrm {H} \mathrm {t}, \mathrm {Z} \mathrm {t}, \mathrm {W}\mathrm {b}$ are presented for various combinations of the $\mathrm {Z}'$ resonance mass and the vector-like $\text {T} $ quark mass. These results represent the most stringent limits to date for the decay mode $\mathrm {Z}'\rightarrow \mathrm {t}\text {T} \rightarrow \mathrm {t}\mathrm {H} \mathrm {t}$ . In a benchmark model with extra dimensions, invoking a heavy spin-1 resonance $\mathrm {G}^* $ , masses of the $\mathrm {G}^* $ between 1.5 and 2.3 $\,\text {TeV}$ and between 2.0 and 2.4 $\,\text {TeV}$ are excluded for $\text {T} $ masses of 1.2 and 1.5 $\,\text {TeV}$ , respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Thermal Management for FPGA Nodes in HPC Systems

The integration of FPGAs into large-scale computing systems is gaining attention. In these systems, real-time data handling for networking, tasks for scientific computing, and machine learning can be executed with customized datapaths on reconfigurable fabric within heterogeneous compute nodes. At the same time, thermal management, particularly battling the cooling cost and guaranteeing the reliability, is a continuing concern. The introduction of new heterogeneous components into HPC nodes only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is less explored. Here, we first show that the thermal behaviors of different FPGAs of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning–based model to capture the thermal behavior of each individual FPGA in the cluster. We then propose two thermal management strategies guided by our thermal model. First, we mitigate thermal variation and hotspots across the cluster by proactive thermal-aware task placement. Under the tested system and benchmarks, we achieve up to 26.4° C and on average 13.3° C system temperature reduction with no performance penalty. Second, we utilize this thermal model to guide HLS parameter tuning at the task design stage to achieve improved thermal response after deployment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Characterization of NiFe oxyhydroxide electrocatalysts by integrated electronic structure calculations and spectroelectrochemistry

NiFe oxyhydroxide materials are highly active electrocatalysts for the oxygen evolution reaction (OER), an important process for carbon-neutral energy storage. Recent spectroscopic and computational studies increasingly support iron as the site of catalytic activity but differ with respect to the relevant iron redox state. A combination of hybrid periodic density functional theory calculations and spectroelectrochemical experiments elucidate the electronic structure and redox thermodynamics of Ni-only and mixed NiFe oxyhydroxide thin-film electrocatalysts. The UV/visible light absorbance of the Ni-only catalyst depends on the applied potential as metal ions in the film are oxidized before the onset of OER activity. In contrast, absorbance changes are negligible in a 25% Fe-doped catalyst up to the onset of OER activity. First-principles calculations of proton-coupled redox potentials and magnetizations reveal that the Ni-only system features oxidation of Ni2+ to Ni3+, followed by oxidation to a mixed Ni3+/4+ state at a potential coincident with the onset of OER activity. Calculations on the 25% Fedoped system show the catalyst is redox inert before the onset of catalysis, which coincides with the formation of Fe4+ and mixed Ni oxidation states. The calculations indicate that introduction of Fe dopants changes the character of the conduction band minimum from Ni-oxide in the Ni-only to predominantly Fe-oxide in the NiFe electrocatalyst. These findings provide a unified experimental and theoretical description of the electrochemical and optical properties of Ni and NiFe oxyhydroxide electrocatalysts and serve as an important benchmark for computational characterization of mixedmetal oxidation states in heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Photo Doppler Velocimetry and Gamma/Neutron Yield Measurements of Godiva-IV Critical Assembly

The purpose of this experiment was to collect data for a dynamic benchmark of the Godiva-IV burst assembly. Data were taken using two different measurement systems. The gamma & neutron flux was measured using a calibrated, high-dynamic-range scintillator detector, the MHD-240. The measurement will be used to determine the total fission yield and alpha throughout the burst and shutdown sequence of Godiva-IV. The Photon Doppler Velocimetry (PDV) measurement detected the surface motion of the burst assembly as a function of time. The combined data will be used in a multi-physics simulation of the Godiva-IV burst assembly.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Flattop-HEU Benchmark Reevaluation Summary

The Flattop critical assembly was first constructed in the 1950’s at Los Alamos National Laboratory as a follow-on to the Topsy experiment. Flattop is composed of a sphere of special nuclear material (SNM) surrounded by a thick spherical reflector made of natural uranium (NU). Two SNM cores currently exist: a highly-enriched-uranium (HEU) core and a plutonium core. The reflector is composed of three parts: a stationary hemisphere and two movable quarter spheres. For fine reactivity control, there are three control rods of NU that are inserted into the stationary hemisphere from underneath the assembly. The final components that allow for reactivity adjustment are the glory hole pieces, mass adjustment buttons, and hemispherical caps. These pieces can be loaded in various configurations to change the available reactivity loaded in the system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Closing the Loop on Automotive Carbon Fiber Prepreg Manufacturing Scrap

The project demonstrated how to “close the loop” on carbon fiber by integrating industrial carbon fiber scrap into new functional components in an automotive lightweighting application. The project serves as a validation of discontinuous recycled carbon fiber in a commercial context, while generating comprehensive material data throughout the production chain. To this end, the project exhibited increasing complexity as material evaluation progressed from benchtop to commercial scale through full-scale part production, with key material properties thoroughly characterized throughout the process. Of particular focus was the form of the fiber that was fed into compounding, as recycled fiber has historically been problematic to feed at commercial-scale. Carbon fiber is energy-intensive to manufacture, so reuse of existing fiber material can reduce costs and increase sustainability. Additionally, by integrating recovered short fiber into a thermoplastic, regrind processes can be used to provide feedstock for later generations of product. While regrind plastics are not “infinitely recyclable”, reusing the manufacturing scrap over several generations of products can greatly increase material sustainability and lower the fractional embodied energy of each successive product. As such, this project supports the IACMI technical goals of (1) 25% lower carbon fiber-reinforced polymer (CFRP) cost, (2) 50% reduction in CFRP embodied energy, and (3) 80% composite recyclability into useful products. The initial stage of the project involved down selecting surface treatment (sizing) chemistries. Sizing evaluations were performed on Vartega’s chemically recycled intermediate modulus fiber along with standard modulus dry scrap which was oversized with sizing provided by Michelman. More dramatic improvements from sizing were found on the standard rather than the intermediate modulus fibers. The strength of the chemically recycled individual fibers were evaluated by Michelman and ORNL through single fiber testing and found to be comparable to similarly evaluated virgin fibers. UDRI’s mechanical testing on injection molded test specimens identified similar mechanical properties and fiber distribution relative to benchmark specimens. Additional surface chemistry tests and visualizations were performed by the Colorado School of Mines to confirm close conformance between the benchmark and recycled-fiber specimens. As the mechanical test results exceeded the 80% threshold established as the go/no-go(GNG), the project scale was increased to use commercial-scale equipment that would both better characterize the manufacturing utility of the target product format and allow qualitative assessment of a complex commercial part. An upscaled compounding evaluation was performed with a 27 mm twin-screw compounding extruding using oversized standard modulus fibers that were formatted to improve bulk solids transfer. The project team anticipated that milestone mechanical benchmarks could be achieved given the favorable performance of the sized standard modulus material identified in the initial micro-compounding trials. While the mechanical performance did meet the milestone target for that phase of the project, mechanical properties for this standard modulus-based compound were still less than those of the Ford specification. To compare the performance, the project team oversized intermediate modulus dry fibers and compounded them with the project resin at BASF using a 40 mm compounder. Test specimen mechanical performance exceeded the targets laid out in both the project milestone and the Ford specification. A series of prototype parts were successfully molded, albeit with instances of short shot components due to the high thermal conductivity of the carbon fiber compared to glass fiber for which the prototype tool was designed for. The project demonstrated that recycled carbon fiber is a viable option in fiber reinforced compound, providing greatly increased strength and modulus for applications that require them. The “agglomerated” format that facilitated effective bulk solids transfer of recovered fiber showed promise for industrial application.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems

Active distribution networks are being challenged by frequent and rapid voltage violations due to renewable energy integration. Conventional model-based voltage control methods rely on accurate parameters of the distribution networks, which are difficult to achieve in practice. This paper proposes a novel physical-model-free two-timescale voltage control framework for active distribution systems. To achieve fast control of PV inverters, the whole network is first partitioned into several subnetworks using voltage-reactive power sensitivity. Then, the scheduling of PV inverters in the multiple sub-networks is formulated as Markov games and solved by a multi-agent soft actor-critic (MASAC) algorithm, where each subnetwork is modeled as an intelligent agent. All agents are trained in a centralized manner to learn a coordinated strategy while being executed based on only local information for fast response. For the slower time-scale control, OLTCs and switched capacitors are coordinated by a single agent-based SAC algorithm using the global information with considering control behaviors of the inverters. Particularly, the two-level agents are trained concurrently with information exchange according to the reward signal calculated from the data-driven surrogate model. Comparative tests with different benchmark methods on IEEE 33-and 123-bus systems and 342-node low voltage distribution system demonstrate that the proposed method can effectively mitigate the fast voltage violations and achieve systematical coordination of different voltage regulation assets without the knowledge of accurate system model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

TH-EF-207A-07: An Integrated X-Ray/bioluminescence Tomography System for Radiation Guidance and Tumor Evaluation

Purpose: CT is not able to differentiate tumors from surrounding soft tissue. This study is to develop a bioluminescence tomography (BLT) system that is integrated onto our previously developed CT guided small animal arc radiation treatment system (iSMAART) to guide radiation, monitor tumor growth and evaluate therapeutic response. Methods: The BLT system employs a CCD camera coupled with a high speed lens, and is aligned orthogonally to the x-ray beam central axis. The two imaging modalities, CT and BLT, are physically registered through geometrical calibration. The CT anatomy provides an accurate contour of animal surface which is used to construct 3D mesh for BLT reconstruction. Bioluminescence projections are captured from multiple angles, once every 45 degree rotation. The diffusion equation based on analytical Kirchhoff approximation is adopted to model the photon propagation in tissues. A discrete cosine transform based reweighted L1-norm regularization (DCT-re-L1) algorithm is used for BLT reconstruction. Experiments are conducted on a mouse orthotopic prostate tumor model (n=12) to evaluate the BLT performance, in terms of its robustness and accuracy in locating and quantifying the bioluminescent tumor cells. Iodinated contrast agent was injected intravenously to delineate the tumor in CT. The tumor location and volume obtained from CT also serve as a benchmark against BLT. Results: With our cutting edge reconstruction algorithm, BLT is able to accurately reconstruct the orthotopic prostate tumors. The tumor center of mass in BLT is within 0.5 mm radial distance of that in CT. The tumor volume in BLT is significantly correlated with that in CT (R2 = 0.81). Conclusion: The BLT can differentiate, localize and quantify tumors. Together with CT, BLT will provide precision radiation guidance and reliable treatment assessment in preclinical cancer research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Horizontal Split Table Conceptual Design for Validation of Nuclear Data used in Advanced Reactors [Slides]

A methodology to create conceptual designs of benchmark critical experiments for advanced reactors nuclear data testing and validation was developed. A first concept was explored, pebble-bed high-temperature gas cooled reactor, based on the HTR-10 reactor. The very high correlation is a proof of concept that the design is similar to the application, and performing such critical experiments would help nuclear data testing and validation. This proof-of-concept was included in the IER-539 CED-1:Preliminary Design of a New Horizontal Split Table report. Other concepts could be explored if needed, such as Molten-salt reactor, Sodium-cooled fast reactor or Heat pipe reactors/Microreactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Ion‐Conducting, Electron‐Blocking Layer for High‐Performance Solid Electrolytes

Lithium metal batteries bring greater promise for energy density, often relying on solid‐state electrolytes to meet critical benchmarks. However, Li dendrite formation is a prevailing problem that limits the cycle life and Coulombic efficiency of solid‐state Li metal batteries. For the first time, a thin (<100 nm) layer of electronically insulating, ionically conducting lithium phosphorus oxynitride (LiPON) is applied using atomic layer deposition between a Li anode and garnet Li 7 La 3 Zr 2 O 12 (LLZO). The performance of a conformal LiPON layer as an electron barrier in symmetric Li‐LLZO cells is observed through potential step chronoamperometry, galvanostatic cycling, electron microscopy, and various spectroscopic techniques. The LiPON‐coated LLZO achieves 100 times lower electronic conductance than LLZO alone. Cycling carried out at 0.1 mA cm −2 for 100 cycles demonstrates that suppression of electron pathways into the bulk solid electrolyte improves the cycle life of a lithium metal cell. These findings suggest an electronic conductivity effect in solid‐state electrolytes. A strategy is demonstrated to design thin‐film (LiPON)‐modulated bulk solid‐state electrolytes (LLZO) capable of maintaining high ionic conductivity and electrochemical stability while reducing the effective electronic conductivity, which results in significantly decreased dendrite formation, improved cycle life, and greater interfacial integrity between the electrolyte and a Li anode.

Hitz, Emily M.↗
DOE OSTI2021

Flattop Benchmark CED-2 (IER-423)

The final design for the Flattop HEU Core Benchmark is presented in this report. Physical measurements will be performed on Flattop components using modern instruments and techniques to define uncertainties necessary to meet contemporary ICSBEP standards. A preliminary re-evaluation of ICSBEP HMF-0028 (Flattop HEU Core) led to the development of IER-423 CED-1, wherein total relative uncertainties in $k_{eff}$ were provided based on a new detailed model. The estimated uncertainty on the total uncertainty is +100%/-0%, given a lack of documented uncertainties on mass, dimensions, and densities of predominantly the natural uranium (NU) and highly enriched uranium (HEU) components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

The BayREN Integrated Commercial Retrofits (BRICR) Project: An Introduction and Preliminary Results

BayREN Integrated Commercial Retrofits (BRICR) is a DOE-funded project which aims to enhance the capacity of energy efficiency programs to recruit participants, develop retrofits, and measure outcomes in small and medium-sized commercial buildings, a sector notoriously hard to reach and expensive to serve, that accounts for 2/3 of US commercial floor space. To address these barriers, BRICR leverages existing incentives, financing, data, and open source software to facilitate two paths for comprehensive improvements: a deep energy retrofit, or serial upgrades integrated into capital improvement and maintenance cycles. BRICR is developing an integrated workflow for iterative energy modeling of commercial buildings for city energy program managers and auditors - starting with mass building-scale simulation based on public records and proceeding through audit, retrofit, and measurement and verification stages. BRICR builds on existing tools including LBNL’s CBES, NREL’s OpenStudio, PNNL’s Audit Template, and DOE’s BuildingSync and SEED PlatformTM. At each stage, BRICR uses available information to inform simulations (starting with public records but iteratively augmented with observations from energy program staff) to improve the quality of the models that inform decision making. This paper presents initial results from energy models of 1699 office and retail buildings in San Francisco. Building stock data from public records were translated to create a BuildingSync file for each building which was stored in SEED. Each BuildingSync file was then translated to multiple OpenStudio Workflow files for EnergyPlus simulation to estimate energy savings of energy conservation measures (ECM). Energy savings predictions for each ECM were written back to an updated BuildingSync file for each building and re-uploaded to SEED. The distribution of baseline energy simulations was calibrated against the publicly disclosed distribution of energy benchmarking data to increase confidence in results.

Piette, M↗
DOE OSTI2025

Warm-phase microphysical evolution in large-eddy simulations of tropical cumulus congestus: evaluating drop size distribution evolution using polarimetry retrievals, in situ measurements, and a thermal-based framework

Owing to uncertainties in convective microphysics processes, improving parameterizations in Earth system models (ESMs) can benefit from observationally constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large-eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP 2 Ex) for evaluating and improving ESMs in single-column model (SCM) mode. We seek observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics initialized with observed aerosol profiles are compared to cloud-top retrievals of cloud droplet effective radius (R eff ), effective variance (ν eff ), and number concentration (N d ) from the airborne Research Scanning Polarimeter (RSP). Both schemes reproduce characteristics of cloud-top N d and R eff that increase and decrease with altitude, respectively. Cloud-top N d is low-biased relative to RSP retrievals in both schemes, potentially due to limitations in both simulations and retrieval assumptions. Cloud-top R eff is low-biased in the bulk scheme but reasonably reproduced by the bin scheme. Profiles of N d and R eff are sensitive to the collision–coalescence process and the vertical variation in aerosol size distribution. Comparison of simulated and in situ droplet size distributions (DSDs) shows that, to first order, integrated moments are always sensitive to sizes < ~ 30 µm and can also be sensitive to larger sizes if the DSDs are sufficiently broad, with implications for the assumed maximum observed size retrieved by the RSP. The bin scheme captures the observed extended tail of the DSD, while the bulk scheme is unable to due to parametric constraints. Differences in expected relationships between in situ measurements of cloud cores and cloud-top retrievals by RSP demonstrate difficulty in constraining well the case presented herein. Finally, a thermal-tracking framework demonstrates that the dilution of N d throughout a thermal's lifetime is heavily determined by collision–coalescence and the height-varying aerosol distribution and that, in the absence of these, the impact of entrainment on diluting N d is largely offset by secondary activation. Implications for evaluating warm-phase convective microphysics schemes in ESMs and translating results for use on global, space-based polarimetry platforms are discussed.

Stanford, McKenna Wallace [Columbia Univ., New Yor↗
DOE OSTI2015

Mapping the Ultrafast Changes of Continuous Shape Measures in Photoexcited Spin Crossover Complexes without Long-Range Order

Establishing a tractable yet complete reaction coordinate for the spin-state interconversion in d(4)-d(7) transition metal complexes is an integral aspect of controlling the dynamics that govern their functionality. For spin crossover phenomena, the limitations of a single-mode approximation that solely accounts for an isotropic increase in the metal-ligand bond length have long been recognized for all but the simple octahedral monodentate FeII compounds. However, identifying the coupled deformations that also impact on the unimolecular rate constants remains experimentally and theoretically challenging, especially for samples that do not display long-range order or when crystallization profoundly alters the dynamics. Owing to the rapid progress in ultrafast X-ray absorption spectroscopy (XAS), it is now possible to obtain transient structural information in any physical phase with unprecedented details. Using picosecond XAS and DFT modeling, the structure adopted by the photoinduced high-spin state of solvated [Fe(terpy)(2)](2+) (terpy: 2,2':6',2 ''-terpyridine) has been recently established. Based on these results, the methodology of the continuous shape measure is applied to classify and quantify the short-lived distortion of the first coordination shell. The reaction coordinate of the spin-state interconversion is clearly identified as a double axial bending. This finding sets a benchmark for gauging the influence of first-sphere and second-sphere interactions in the family of FeII complexes that incorporate terpy derivatives. Some implications for the optimization of related photoactive FeII complexes are also outlined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL) proved to be effective in optimizing the management of integrated energy systems in buildings, reducing energy costs and improving indoor comfort conditions when compared to traditional reactive controllers. However, the scalability and implementation of DRL controllers are still limited since they require a considerable amount of time before converging to a near-optimal solution. This issue is currently addressed in literature through the offline pre-training of the DRL agent. However this solution results in two main critical issues: (1) the need to develop a building surrogate model to perform the training task, and (2) the need to perform a fine-tuning process over several training episodes to obtain a near-optimal control policy. In this context, this paper introduces an Online Transfer Learning (OTL) strategy that exploits two knowledge-sharing techniques, weight-initialization and imitation learning, to transfer a DRL control policy from a source office building to various target buildings in a simulation environment coupling EnergyPlus and Python. A DRL controller based on discrete Soft Actor–Critic (SAC) is trained on the source building to manage the operation of a cooling system consisting of a chiller and a thermal storage. Several target buildings are defined to benchmark the performance of the OTL strategy with that of a Rule-Based Controller (RBC) and two DRL-based control strategies, deployed in offline and online fashion. The strategy adopted for OTL emulates the real world implementation with a simulation process by implementing the transferred DRL agent for a single episode in the target buildings. Target buildings have the same geometrical features and are served by the same energy system as the source building, but differ in terms of weather conditions, electricity price schedules, occupancy patterns, and building envelope efficiency levels. The results show that the OTL strategy can reduce the cumulated sum of temperature violations on average by 50% and 80% respectively when compared to RBC and online DRL while enhancing the energy system operation with electricity cost savings ranging between 20% and 40%. Furthermore, the OTL agent performs slightly worse than the offline DRL controller but it does not require any modeling effort and can be implemented directly on target buildings emulating a real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Sandia 7uPCX Critical Experiments Exploring the Effects of Fuel-to-Water Ratio Variations

The Sandia Critical Experiments (SCX) Program provides a specialized facility for performing water moderated and reflected critical experiments with UO 2 fuel rod arrays. A history of safe reactor operations and flexibility in reactor core configuration has resulted in the completion of several benchmark critical experiment evaluations that are published in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The LEUCOMP-THERM-078 and LEU-COMP-THERM-080 evaluations from the handbook provide similar cases for reference. The set of experiments described here were performed using the Seven Percent Critical Experiment (7uPCX) fuel to measure the effects of decreasing the fuel-to-water volume ratio on the critical array size. This was accomplished by using fuel loading patterns to effectively increase the pitch of the fuel arrays in the assembly. The fuel rod pitch variations provided assembly configurations that ranged from strongly undermoderated to slightly overmoderated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W m -2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m -2 , respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales.

54 ENVIRONMENTAL SCIENCES↗